In information searching, many search queries are ambiguous. Ambiguity in the context of search exists when a number of possible interpretations may exist for a given query.
A query is a description of a user's search need. For web searching, a query is typically a short sequence of words that the user thinks describe the relevant document or would be in the relevant document. For email searching, a query may be words the user thinks describe the relevant email, or may be in the relevant email, such as: the name of the writer of the email; the email address of the writer of the email; the names of others who also received the email; or other information. For image searching, a query may be words which describe the image, words which may be on the same page as the image, an image which is ‘like’ the target image, or the like.
A document is a unit of information returned in response to a search query. For web searching, a basic document is a web page, it may for example be a web page containing a news story. For email searching, a basic document is an email. For image searching, a basic document is an image. A document may also be a log of the queries in a user search session. Fragments of these units are also considered to be ‘documents’, i.e. our unit of information may be a paragraph from a web page or email, or a portion of an image. A document may also be a session of user search queries.
Searching documents, generally involves looking at the words or the content of the document. What is needed is a technique for more intelligently searching such databases.
Documents with time stamps, such as news stories and emails, are an important source of information that people access daily. Traditional tools for searching these collections either ignore the temporal information, sorting by content relevance to the query, or use the timestamps simply to allow the user to sort by chronological order. Traditional methods for detailing with temporal information are inadequate in their understanding of when a query is temporally structured and dealing with a query when it is temporally structured.
What is needed is a system that does not merely construct timelines from arbitrary sets of documents, but instead a system that is able to implement this task in the context of search refinement, when appropriate. What is needed is a system that predicts when a user is interested in temporally structured information. Further, what is needed is a system that is able to present a summary of that information and to obtain feedback from the user.